Mapping Climate and Ecological Anomalies as a Veritable Tool for Planning Eco-Climate Resilience in Northern Nigeria

Abstract The Northern Nigeria savanna ecological zone is vulnerable to eco-climatic anomalies driven by climate change and land degradation. Despite previous studies on individual climate stressors, there are few studies on sub-national and spatial Eco-Climatic Resilience Index (ECRI) that integrate biophysical and social factors across the region, which limits targeted climate adaptation planning. This study applied Mann-Kendall rainfall trend analysis and the Sen slope test to rainfall data acquired from the Nigeria Meteorological Agency (NIMET) across 19 stations from 1971 to 2023. A four-stage cluster sampling design was employed to sample 2,400 farming households from 48 communities in the study regions. A Principal Component Analysis (PCA) was applied to reduce the dimensionality of the data from 46 variables across climatic anomalies, ecological anomalies, exposure, sensitivity, adaptation capacity, and transformational adaptation capacity. Community PCA scores were interpolated and integrated into the composite ECRI, and the composite was classified into five resilience zones. The findings revealed a spatial mixed trend in rainfall as stations in the Sudan-Sahelian savanna showed both significant and insignificant upward trends, with the highest rate of change recorded in Kano (+17.89 mm/year), while stations in the Guinea Savanna indicate a significant and insignificant downward trend, with the highest rate of change recorded in Makurdi (−26.43 mm/year). Although the stations in Sudan-Sahelian showed upward rainfall trends, the ECRI map depicted a north-south resilience gradient, with very low resilience across the Sahelian savanna north and very high resilience across the Guinea Savanna south. Overall, the climate and ecological stressors were strongly related (r = 0.82). These findings imply that increased rainfall does not necessarily translate into improved climate resilience. The varying resilience levels depicted by ECRI signal the need for state/location-specific transformation/adaptation strategies to build individual, community, and state capacity for more resilient livelihoods across the study region and similar regions with similar socio-economic and climate characteristics.